Découvrez les skills databases bioinformatics, comparez leurs dépôts et consultez leurs instructions.
Load single-cell TCR-seq or scBCR-seq data from various formats into a scRepertoire-compatible object. This process reads VDJ (variable, diversity, joining) receptor contig data from multiple single-cell sequen...
Separates T and non-T cells or B and non-B cells from a mixed cell population. Uses either clonotype percentage from VDJ data, indicator gene expression (CD3 markers for T cells, CD19/CD20 for B cells), custom...
Performs unsupervised clustering on single-cell RNA-seq data using Seurat. This process finds nearest neighbors, computes UMAP for visualization, and applies Louvain/Leiden algorithms to identify cell clusters....
Imputes missing/dropout values in scRNA-seq expression data to improve metabolic pathway analysis. This process handles sparsity common in single-cell RNA sequencing data by filling in zero values using advance...
Annotates cell clusters with biological cell type labels using multiple methods: direct assignment, ScType, scCATCH, hitype, or CellTypist. This process is essential for interpreting clustering results by assig...
Comprehensive metabolic landscape analysis pipeline for scRNA-seq data. This is an all-in-one process group performing complete metabolic pathway analysis including expression imputation, feature selection, pat...
Performs coarse clustering on ALL cells (including T cells, B cells, and non-T/B cells) before cell type selection. This process identifies broad cell populations to enable subsequent T/B cell selection via `TO...
Finds marker genes for clusters of ALL cells before T/B cell selection. This process identifies differentially expressed genes across unsupervised clusters to help identify broad cell types (T cells, B cells, M...
Finds differentially expressed genes (markers) for clusters of T/B cells using Seurat's FindMarkers function. Performs statistical testing between clusters, identifies cluster-defining genes, and automatically...
Performs pseudo-bulk differential gene expression analysis using DESeq2 or edgeR. Aggregates single-cell counts to sample-level pseudo-bulk data, then identifies differentially expressed genes between condition...
Analyzes metabolic pathway heterogeneity within cell populations by calculating normalized enrichment scores (NES) for each pathway across different groups. Quantifies metabolic diversity and identifies pathway...
Infer ligand-receptor interactions and cell-cell communication networks from single-cell RNA-seq data using the LIANA+ framework. Identifies potential signaling events between cell types based on gene expressio...
Extract patterns and generalizations from multiple observations. Use when detecting recurring themes, building predictive rules, or identifying systemic behaviors from accumulated data. Produces validated patte...
Graceful memory compression with integrity — summarize before forgetting, never fabricate
Big-endian file naming as semantic binding
Structured task decomposition and tracking.
Export Pixel Detective UMAP projections with HDBSCAN and manage Qdrant collections via the ingestion API. Use when the user asks for latent space exports, UMAP clustering assets, or collection operations (list/...
TAM/SAM/SOM calculation, competitor analysis, and market trends identification. Use when analyzing markets, validating business ideas, or entering new markets.
Opentrons Thermocycler Module - automated PCR thermal cycling with independent block (4-99°C) and lid (37-110°C) temperature control, profile execution, and auto-sealing lid support (GEN2) for high-throughput m...
Perform statistical hypothesis testing, regression analysis, ANOVA, and t-tests with plain-English interpretations and visualizations.
Predicts potential off-target sites for a given sgRNA sequence using mismatch analysis.
Pathway enrichment analysis using gcell. Use this skill when users ask about: - Gene set enrichment analysis - GO (Gene Ontology) enrichment - KEGG pathway analysis - Reactome pathway enrichment - Custom pathwa...
ChIP-Atlas epigenome data query using gcell. Use this skill when users ask about: - Finding ChIP-seq, ATAC-seq, or DNase-seq experiments - Searching for transcription factor binding data - Finding histone modif...
DNA sequence and motif analysis using gcell. Use this skill when users ask about: - Loading and manipulating DNA sequences - Genome assembly access (hg38, hg19, mm10) - Motif scanning with HOCOMOCO motifs - Wor...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.